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  • Table of Content
       , Volume 28 Issue 4 Previous Issue    Next Issue
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    Review
    Active microwave scattering models used in soil moisture retrieval
    LI Li, WANG Di, PAN Caixia, NIU Huanna
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 1-9.   DOI: 10.6046/gtzyyg.2016.04.01
    Abstract   HTML   PDF (769KB) ( 820 )

    As an important component of the surface water cycle, soil moisture content monitoring has become one of the research hotspot in such fields as hydrology, meteorology, agriculture and ecological environment. In precision irrigation, drought monitoring and crop estimations, soil moisture content monitoring has shown especially significant practical significance. The close relationship between microwave scattering intensity and soil moisture makes the active microwave remote sensing technology one of the most effective methods for monitoring soil moisture with high spatial resolution. The lack of high performance microwave scattering models is a main factor restricting the application of soil moisture retrieval. For the bare soil surface and vegetation cover surface, microwave scattering models are analyzed firstly. Then the influence factors of soil moisture retrieval are discussed. And when the application examples are shown, the calibration methods for main influence factors are analyzed and summarized.

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    Review of methods on estimation of daily evapotranspiration from one time-of-day remotely sensed transient evapotranspiration
    LIU Suhua, TIAN Jing, MI Sujuan
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 10-17.   DOI: 10.6046/gtzyyg.2016.04.02
    Abstract   HTML   PDF (741KB) ( 790 )

    Remote sensing is a main method for obtaining large-scale land surface evaportransporation (ET), and the direct result of ET is an instantaneous value estimated at the passing time of satellite. Therefore only the daily evapotranspiration has practical significance. Recently, many ET time scale extrapolation methods have been proposed, such as constant evaporative fraction method, time integration method, sinusoid method, crop coefficient method and canopy resistance method. In order to provide readers with clear outlines about the methods and tell readers what is the proper justification when these methods are used, this paper attempted to summarize and make a comparison of the above 5 common methods based on their principles and characteristics. The results obtained show that each method has its own advantages and disadvantages, and hence researchers should consider features of the study area and the data to assure the best selection. What's more, there is a summarization about the existing difficulties and the research hotspots.

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    Technology and Methodology
    A study of SNR index setting of infrared imager based on spectrum simulation
    WEI Dandan, GAN Fuping, ZHANG Zhenhua, XIAO Chenchao, TANG Shaofan, ZHAO Huijie
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 18-23.   DOI: 10.6046/gtzyyg.2016.04.03
    Abstract   HTML   PDF (3469KB) ( 462 )

    Signal to noise ratio(SNR) is regarded as an essential parameter of sensors and remote sensing images. It is an important indicator of the acquired digital signal's trueness. The level of SNRs plays a critical role in remote sensing data's applications. The parameter setting should focus on satisfying the users' requirement, so it is necessary to carry out the study of SNR index setting of infrared imager based on spectrum simulation. In this paper, the radioactive transfer model and spectral library were used to simulate apparent radiance and different levels of additive white Gaussian noise was added to the simulated spectrum. The simulated spectrum was re-sampled according to the spectral response function calculated from the designed sensor. In the section of noise impact on object recognition, spectral feature fitting was chosen to compare the fit of simulated spectra with different noise levels to reference apparent radiance spectra without noise. For various accuracies of objects recognition demand in different domains, the authors can propose different suggestions to users, and this research provides reasonable and scientific foundation for sensor design work.

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    Radiometric calibration method of thermal-infrared images based on on-orbit classification and statistics
    ZHANG Bingxian, LI Yan, HE Hongyan
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 24-29.   DOI: 10.6046/gtzyyg.2016.04.04
    Abstract   HTML   PDF (3656KB) ( 540 )

    Relative radiometric calibration precision will affect the application of satellite images, and hence high precision relative radiometric is very important. Nowadays, the ordinary radiometric calibration method of the thermal-infrared images is the on-orbit radiometric calibration which has fewer sample data and lower accuracy, therefore the result of on-orbit radiometric calibration can't satisfy the application requirement. In view of such a situation, a new radiometric calibration method of the thermal-infrared images based on classification and statistics is proposed in this paper. The new method adopts the original satellite images as sample data to calculate the parameters based on rich types of surface feature in satellite images to solve the problem of insufficient sample data of on-orbit radiometric calibration, meanwhile it introduces classification into the construction of the new calibration model by considering the different characteristics of photoelectric response function that the satellite payload will have in different radiometric energy so as to improve the precision of radiometric calibration. The experimental results show that the proposed method performs better than the ordinary on-orbit radiometric calibration method.

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    Absolute radiometric calibration of level-1 detected ground range products of new SAR sensors
    DU Weina, XU Aigong, SONG Yaoxin, SUN Huasheng
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 30-34.   DOI: 10.6046/gtzyyg.2016.04.05
    Abstract   HTML   PDF (1923KB) ( 511 )

    For the current situation of the lack of the new SAR sensor data preprocessing software, this paper introduced in detail the methods of absolute radiometric calibration and the parameter acquisition for several new SAR sensor level-1 detected products, such as ENVISAT ASAR,Radarsat2,Cosmoskymed,TerraSAR-X and Sentinel1. In addition, the absolute radiometric calibration process was achieved by programming with the level-1 detected ground range products(L-1 DGRP) data of Sentinel1 sensor, and C++ programming language was used to achieve the absolute radiation of the calibration process. At last, the radiometric calibration results produced by the method developed in this paper and implemented in the authors' software were compared with those by ESA S1 ToolBox, the freely distributed SAR data processing tool by European Space Agency, and it is shown that the two numerical back scattering systems are basically the same. The radiometric calibration method developed in this paper is proved to be correct by the program implementation.

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    Expanding research on CSG in 3D reconstruction from LiDAR
    ZHA Dajian, LI Lelin, JIANG Wangshou, HAN Yongshun
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 35-42.   DOI: 10.6046/gtzyyg.2016.04.06
    Abstract   HTML   PDF (5617KB) ( 621 )

    To tackling such problems as primitive decomposition, primitive recognition, model integration in 3D model reconstruction with LiDAR data by using the CSG method, this paper proposes an expanding method for CSG. In this method, the clustering property of building contours is used for layers partition and primitives decomposition, then the styles of the primitives is recognized by combining the features of contours clusters and the contour reconstruction results. In this way, the process of primitives automatic recognition in CSG method is achieved. According to the primitive recognition result, the corresponding reconstruction method for the segmentation is selected, and the whole 3D model for complex building is automatically reconstructed by integrating the segmentation models based on a set of effective model integration rules at last. Experiment results of a wide range LiDAR data show that the proposed expanding CSG method is effective in the 3D reconstruction of complex buildings with LiDAR data.

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    Facade extraction from oblique point cloud considering geometrical and color information
    ZHOU Hanghang, ZOU Zhengrong, ZHANG Yunsheng, ZHENG Te
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 43-48.   DOI: 10.6046/gtzyyg.2016.04.07
    Abstract   HTML   PDF (9748KB) ( 474 )

    Aimed at tackling the difficulty in extracting facade from point cloud derived from dense matching of multi-angle airborne oblique images, this paper proposes a facade extraction method considering point cloud geometrical and color information. This method calculates normal vector for each point in the point cloud, and then uses the orientation of the normal vector for initial facade segmentation. After that, color information is used to remove point cloud about vegetation. On the basis of the initial result, the remaining ground points are removed. Finally, clustering analysis is used to refine the result, and facade point cloud can be obtained. Two groups of data sets are used for experiments, and the results reveal that the proposed method can automatically extract the facade of the building, with the completeness and correctness up to 90%, and the accuracy is more than 83%, thus providing the basis for the subsequent facade reconstruction.

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    Supervised evaluation of optimal segmentation scale with object-oriented method in remote sensing image
    ZHUANG Xiyang, ZHAO Shuhe, CHEN Cheng, CONG Dianmin, QU Yongchao
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 49-58.   DOI: 10.6046/gtzyyg.2016.04.08
    Abstract   HTML   PDF (11535KB) ( 501 )

    The object-oriented classification quality of the remote sensing images depends not only on the classification algorithm but also on the goodness of the segmentation results. The quality of image segmentation determines the accuracy of subsequent classification of the remote sensing images. The quantitative method for determining the optimal segmentation scale and eliminating the interference of subjective factors becomes the focus of the image segmentation quality assessment. However, the importance of object recognition in image segmentation quality evaluation is often ignored in the previous segmentation quality evaluation method. After analyzing the complex spatial relations between the image objects and the actual image region, a new optimal segmentation scale evaluation index based on the area and position of the image object was proposed to evaluate the optimal segmentation scale. Based on the evaluation index, a WorldView2 multispectral image was used to be researched and the optimal segmentation parameters were determined. The results show that the segmentation scale evaluation index is effective in image segmentation quality assessment and parameter optimization. The experimental results have also shown the effectiveness of the method proposed in this paper for both segmentation quality assessment and optimal parameter selection. Also, the procedure of segmentation quality assessment can be conducted with less human intervention, making the result more objective.

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    Selection of best-fitting scale parameters in image segmentation based on multiscale segmentation image database
    ZHANG Tao, YANG Xiaomei, TONG Liqiang, HE Peng
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 59-63.   DOI: 10.6046/gtzyyg.2016.04.09
    Abstract   HTML   PDF (6070KB) ( 683 )

    Finding the best-fitting parameters in image segmentation is of great importance for object-oriented information extraction. The try-and-error strategy and visual analysis on multiresolution segmentation are widely used in real practice, but they cannot analyze a large number of segmentation results. This paper proposes a procedure for picking segmentation parameters based on multiresolution segmentation image database and visual analysis. The experiment of multiresolution segmentation on SPOT5 image shows that the proposed procedure is capable of finding the best fitting parameters. The procedure is more efficient and effective than the traditional try-and-error strategy, and there is good potential for the procedure to be used in practical image analysis application.

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    A new method for classification of high spatial resolution remotely sensed imagery based on fusion of shape and spectral information of pixels
    YANG Qingshan, ZHANG Hua
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 64-70.   DOI: 10.6046/gtzyyg.2016.04.10
    Abstract   HTML   PDF (9533KB) ( 381 )

    In the classification of high spatial resolution remotely sensed imagery,due to the presence of the same object with different spectra, the dependence only on spectral information for classification is not enough. To improve the accuracy of classification, the authors proposed a novel spatial features extraction method for classification of the HSRMI. Firstly, neighborhood pixels' spatial relationship was described and used to calculate and extract the pixel homogeneous regions (PHR). Then, based on the extracted PHR, the pixels' shape index features, including length-width ratio(LW) and area-perimeter ratio(PAI), were extracted. Lastly, the pixel shape index features were normalized and combined with the spectral information to perform classification by using SVM classification method. Two different areas' QuickBird images were used to test the performance of proposed method. The experimental results show that the proposed method has the highest performance compared with pixel shape index(PSI) and spectral information, and can improve the classification accuracy of high spatial resolution remotely sensed imagery.

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    Remote sensing image classification based on G statistics of object histogram
    LI Liang, LIANG Bin, XUE Peng, YING Guowei
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 71-76.   DOI: 10.6046/gtzyyg.2016.04.11
    Abstract   HTML   PDF (4089KB) ( 448 )

    In order to make full use of the spectral feature of the object, this paper proposes a classification method for remote sensing image based on G statistics of the object histogram. Image objects were obtained by multi-resolution image segmentation method. Then training objects were chosen from these objects. The histogram of the object was obtained with the adaptive gray level according to the spectral property. G statistics was used to measure the histogram distance between test object and training object which describes the heterogeneity of two objects. Minimum distance classifier was employed to get the image classification result. The experiment on the remote sensing image shows that the proposed method can improve the accuracy of the classification.

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    Knowledge driven change detection method for aircraft targets
    XIANG Shengwen, WEN Gongjian, GAO Feng
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 77-82.   DOI: 10.6046/gtzyyg.2016.04.12
    Abstract   HTML   PDF (3676KB) ( 870 )

    Aimed at high-resolution optical sense images, this paper proposes a knowledge driven change detection method for the aircraft targets. First, a spatial mask image of the airport is set up according to the geographical position information and the candidate area of aircraft targets is obtained. Second, the control points' information in the target area is utilized to register input images. As changes of aircraft targets can lead to significant texture changes in area, the authors detected the changes by extracting texture features. A weak texture elimination and edge suppression method was put forward to reduce the false-alarm rate. Finally, the mathematical morphological operation method was employed to eliminate some isolation points and acquire the detection results. Experiments show that the proposed method can efficiently reduce the false-alarm caused by registration error and skirt response, with the detection rate of aircraft targets reaching 92.47%.

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    Algorithm of Bowtie effect rapid removing for low and medium resolution satellite images
    JIA Yi, WANG Sheng, JIANG Wanshou
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 83-87.   DOI: 10.6046/gtzyyg.2016.04.13
    Abstract   HTML   PDF (3230KB) ( 568 )

    Bowtie effect is a data overlapping phenomenon which arises in low and middle resolution satellite images such as FY-3 and MODIS. This effect restricts the further application of the satellite image data, so it must be removed before using these data. In view of the defects of existing methods for Bowtie effect removing such as complex calculation and low efficiency, this paper proposes a geometric correction algorithm based on path tracking to remove bowtie effect. It can quickly locate the pixel position of corrected image in the original image by path tracking while considering the disposal of the area which crosses the meridian or fluctuant. The experimental results show that this method can remove the Bowtie effect effectively and quickly.

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    An improved method for atmospheric transmissivity inversion based on field atmospheric modes
    HAN Liang, DAI Xiaoai, SHAO Huaiyong, WANG Hongyan
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 88-92.   DOI: 10.6046/gtzyyg.2016.04.14
    Abstract   HTML   PDF (1062KB) ( 582 )

    When the land surface temperature(LST) is inverted by using mono-window algorithm, it is difficult to obtain atmospheric transmissivity when detailed atmospheric profile data are absent. In this study, an atmospheric transmissivity inversion method was improved using three basic parameters comprising near-surface temperature, relative humidity and atmospheric pressure based on the field atmospheric modes. The authors established the corresponding equations to estimate atmospheric transmittance when the atmospheric moisture content exceeds 0.4~3.0 g·cm-2. On such a basis, the authors monitored the atmospheric transmissivity changes on nationwide scale. The results of the study show that the method proposed in this paper has very high precision under the condition of lower atmospheric moisture content. The precision of LST is improved by about 25% to 71%, and only when the relative error is between 1.33% and 4.07%, the LST produces error between 0.2℃ and 0.6℃.

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    On-orbit MTF estimation and restoration of GF-2 satellite image
    WANG Zhizhong, ZHANG Qingjun
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 93-99.   DOI: 10.6046/gtzyyg.2016.04.15
    Abstract   HTML   PDF (2313KB) ( 467 )

    Modulation transfer function(MTF) is not only an efficient method for monitoring the on-orbit satellite operation status and performance but also an important parameter which is often used to restore satellite image. In this paper, the knife edge method was used to measure the on-orbit MTF of GF-2 satellite panchromatic camera. During the calculation of MTF, Hamming window was used in the process of clipping the line spread function(LSF) in order to restrain the leak of frequency spectrum. Besides, the authors expanded the LSF with zeros so as to improve the sampling frequency during the Fourier transform. The experimental results show that the sampling density of MTF using the knife edge method proposed in this paper is 5 times more than that of the traditional method and the MTF curve is also smoother compared with that of the traditional method. Therefore, the more accurate MTF matrix value can be obtained to improve the performance of image restoration by this method. In this paper, the Wiener filtering method was used to restore the GF-2 satellite panchromatic image with the MTF matrix value. The experimental results also show that the MTF matrices computed by the two methods can all improve the clearness and object edge information of the image. However, the image restored by the MTF matrix values of the authors' method is superior to that of the traditional method in such characteristics as contrast, edge energy and average gradient.

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    Geo-positioning accuracy analysis for domestic high-resolution satellite imagery
    HAN Jie, XIE Yong, WU Guoxi, LIU Qiyue, GAO Hailiang, GUAN Xiaoguo
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 100-107.   DOI: 10.6046/gtzyyg.2016.04.16
    Abstract   HTML   PDF (6306KB) ( 856 )

    The geo-positioning accuracy of domestic high-resolution satellite imagery is a hotspot problem that has attracted much attention among researchers. In this paper, GF-1 and ZY-3 satellite images were treated as investigated objects. After detecting the system error of domestic high-resolution satellite imagery rational polynomial coefficierts(RPCs), using the rational function model(RFM) bundle adjustment method based on the affine model in image space the three-dimensional geo-positioning system errors of stereo image pairs from one single satellite platform were eliminated. The geo-positioning accuracy of domestic high-resolution satellite imagery was comprehensively analyzed, including the geo-positioning accuracy of single scene and stereo image pairs from single and different satellite platforms. Finally, the main factors affecting the geo-positioning accuracy of domestic high-resolution imagery was discussed, and the results obtained by the authors would provide some useful reference information to realize the domestic satellites joint observations.

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    Research on fusion of GF-2 imagery and quality evaluation
    SUN Pan, DONG Yusen, CHEN Weitao, MA Jiao, ZOU Yi, WANG Jinpeng, CHEN Hua
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 108-113.   DOI: 10.6046/gtzyyg.2016.04.17
    Abstract   HTML   PDF (5589KB) ( 871 )

    GaoFen-2 (GF-2) is the first sub-meter civilian optical remote sensing satellite of China configured with 0.81 m resolution panchromatic cameras and 3.24 m multi-spectral cameras. Researches on image fusion algorithm suitable for GF-2 would have great significance for improving the image quality and expanding the application scope of the satellite. Four GF-2 images covering Northeast China from November 22 to 27, 2014 were used in this paper. The authors compared the efficiency of five fusion algorithms, which include component transform (PCA), Gram-Schmidt (GS), modified-HIS transform, HPF and HCS transform algorithm. In order to quantitatively assess the quality of the fused images, the authors adopted the following steps: The authors first examined the visual qualitative result and then evaluated the correlation between the original multi-spectral and the fused images. The authors compared the fused image with the original image in degree of distortion and parts of the statistical parameters such as entropy, average grads and correlation coefficient of the various frequency bands. Finally, the authors performed a supervised classification for the fused images, and compared the accuracies of resulting images. The result shows that all the fusion techniques improve the resolution and the visual effect. The HCS and GS transform algorithm could not only achieve the best results but also have no limit to the number of bands, and hence it is the most suitable method for the GF-2 image fusion. The HPF method is next only to the HCS transform method in the spatial detail enhancement, but the spectral fidelity is the worst among the five image fusion algorithms. It is moderate for the performance of the PCA and modified-IHS transform method, and then these algorithms can provide backup for the GF-2 image fusion.

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    Technology Application
    Extraction of remote sensing information for lake salinity level based on SVM: A case from Badain Jaran desert in Inner Mongolia
    DIAO Shujuan, LIU Chunling, ZHANG Tao, HE Peng, GUO Zhaocheng, TU Jienan
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 114-118.   DOI: 10.6046/gtzyyg.2016.04.18
    Abstract   HTML   PDF (4078KB) ( 756 )

    According to the problems of remote sensing information extraction in lake salinity level of Badain Jaran desert, the authors put forward a method based on support vector machine (SVM). In this paper, the authors adopted Landsat8 OLI remote sensing image as the data source, completed the image preprocessing such as geometric correction, image registration and mosaicking. With the help of the RS and GIS technology, the authors successfully extracted the information of lake salinity levels of the Badain Jaran desert. The results show that the proposed method can effectively solve the problems of less samples and the information extraction of lake salinity levels when the spectral information is confused, and hence has the reference value and can be promoted to other similar situations.

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    Characteristics and influencing factors of land subsidence in Caofeidian Newly-developed Area based on PSInSAR technique
    LI Man, GE Daqing, ZHANG Ling, LIU Bin, GUO Xiaofang, WANG Yan
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 119-126.   DOI: 10.6046/gtzyyg.2016.04.19
    Abstract   HTML   PDF (11787KB) ( 383 )

    The rapid development of land subsidence in Caofeidian area has threatened its function as international transport and commercial trade center, and this area has become one of the most serious areas in Tangshan. Therefore it is very important to comprehensively understand land subsidence distribution of Caofeidian Newly-development Area, especially to grasp main control factors of different subsidence regions. Based on medium and high resolution radar data, the authors obtained whole land cumulative subsidence condition of Caofeidian Newly-development Area by PSInSAR. The results show that the overall surface subsidence is generally more than 77 mm, and there are a couple of typical land subsidence abnormal places in the southwest of Caofeidian Area and in the middle and south of Caofeidian Industry Zone. Moreover, the subsidence gradients in subsidence cone centers are larger. According to site survey, it can be found that the complicated geological condition is an objective factor resulting in land subsidence, and over-extraction of groundwater and large-scale engineering disturbance seem to be the external factors that induce and accelerate land subsidence in Caofeidian Newly-development Area.

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    A study of urban area extraction with the modified human settlement index
    YANG Xiaonan, XU Yun, TIAN Yugang
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 127-134.   DOI: 10.6046/gtzyyg.2016.04.20
    Abstract   HTML   PDF (7681KB) ( 813 )

    Urban areas extraction at regional and global scales remains a challenge. To map urban areas using DMSP-OLS nighttime light data is limited due to the saturation of data values, especially in urban cores. Different nighttime facula sizes lead to different degrees of light overflow, which causes difficulty for quantitative analysis. Vegetation-rich areas are selected to avoid the impact of bare soil when visible-near infrared image is used to map urban. To solve the problems above, this paper proposes modified human settlement index (MHSI) on the basis of human settlement index (HSI), which is composed of DMSP-OLS nighttime light data and visible-near infrared image. The MHSI has been tested in China and USA and testified by using the China city statistical data and USA NLCD land cover data. The results indicate that MHSI can overcome the overflow problem effectively and discriminate urban areas from other feature types such as bare soil, water and vegetable. MHSI can extract the regional or global city areas completely, and the accuracy is better than that of HSI and MODIS land cover data sets.

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    Vehicle identification from remote sensing image based on image symmetry
    CHEN Ren, HUANG Huixian, TAN Yuan, WANG Chengxiao
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 135-140.   DOI: 10.6046/gtzyyg.2016.04.21
    Abstract   HTML   PDF (2041KB) ( 884 )

    The plan view of the vehicle image is symmetrical, which leads to the existence of repeated characteristics in the image. In view of such a situation, the authors present an optimal selection method for Haar-like features. Within the detection window, the two types of features are selected: a half of the detection window's height is taken, and then all the rectangular features are extracted; in the original detection window, only the features that are symmetrical about the symmetry axis of detection window are used, and the upper and lower parts' difference is described. We can fully express the image information and also reduce the repetitive characteristics by using this method. The cascade classifier is trained by extracting these features in samples' grayscale and saturation images, while each layer is trained by using AdaBoost algorithm. The experimental results show that the proposed approach can significantly reduce the number of features and improve the training speed, thus achieving good recognition results.

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    Application of ZY-1 02C satellite data to hydrogeological investigation in Zanda area, Tibet
    LI Xiaomin, YAN Yunpeng, LIU Gang, LI Dongling, ZHANG Xing, ZHUANG Yongcheng
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 141-148.   DOI: 10.6046/gtzyyg.2016.04.22
    Abstract   HTML   PDF (11196KB) ( 550 )

    In order to bring the potential of satellite data for hydrogeology into full play in China, the authors used satellite data of ZY-1 02C to investigate the hydrogeology in Zanda area of Tibet. The authors found 29 springs and spring groups, 14 groundwater discharge zones of different sizes, 3 water-controlling faults and 13 wetlands. And the six types of groundwater comprising pore water in the loose rock, fracture-pore water in the clastic rock, fracture - pore water in the layered rock, fissure karst water, fissure water in the massive rock and freezing layer water were recognized seperately. The genetic type of the Quaternary was divided in detail, and the rich area, general area and poor area of pore water in the loose rock were interpreted. The results of the investigation show that using remote sensing technology in the preliminary work of hydrogeological investigation can greatly reduce workload in the field. It can provide the basic hydrological data for the subsequent detailed hydrogeological survey, thus showing application value of ZY-1 02C satellite data in hydrogeological investigation.

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    Feature description and extraction of residential area based on variogram function and grid division
    ZHANG Enbing, QIN Kun, YUE Mengxue, ZHANG Ye, ZENG Cheng
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 149-155.   DOI: 10.6046/gtzyyg.2016.04.23
    Abstract   HTML   PDF (5032KB) ( 747 )

    As an effective method for describing texture structure, variogram has a good application in residential areas extraction from high-resolution remote sensing image. However, nowadays, residential areas extraction methods mostly apply the calculation in pixel level by moving window, thus the computational efficiency tends to be lower when encountering large images. In addition, when describing texture structure characteristics for different data sources, it has a poor robustness and efficiency for selecting parameters. Therefore, the authors propose an effective method for residential area extraction based on variogram function and grid division in this paper. Firstly, the original image was divided into small grid units and then the unit was taken as the processing object;meanwhile, the optimal description parameters were selected based on the texture difference curve. Finally, the calculated texture characteristics were used to extract residential areas. The experimental results show that the proposed method has better spatial structure description capability and calculation efficiency.

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    Land cover information extraction from remote sensing images using object-based image analysis method integrated with decision tree
    SUN Yuyi, ZHAO Junli, WANG Miaomiao, LIU Yong
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 156-163.   DOI: 10.6046/gtzyyg.2016.04.24
    Abstract   HTML   PDF (2329KB) ( 586 )

    Object-based image analysis, which has been developed rapidly over the last decades, performs advantageous over classic pixel-based image classification. One of the key problems within this paradigm is to automatically build robust and transferable rule sets for segment classification. It has been identified promisingly to develop rule sets by means of decision tree based on data mining. The authors suggest a decision tree model integrated with J48 algorithm embedded in Weka to select parameters from a set of spectral, textural and terrain features relevant to rule sets for segment classification. Based on this method, the authors used Landsat5 TM image data and ASTER digital elevation model to establish land cover classification in the study area, i.e., Baicaoyuan area in Huining county, Gansu Province. Rule sets developed in this way perform acceptable robustness and transferability. Accuracy assessment proves that this method has significantly higher classification accuracy than other pixel-based methods based on employing maximum likelihood and objected-based nearest neighbor logic.

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    An improved length variable angle chain code algorithm and its application to dock identification
    ZHANG Yongmei, YANG Fei, XU Jing
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 164-169.   DOI: 10.6046/gtzyyg.2016.04.25
    Abstract   HTML   PDF (1855KB) ( 644 )

    This paper proposed an improved length variable angle chain code algorithm for the angle information loss of curve approximation and used this algorithm in dock detection. The new algorithm changes the rules in the selection of the end point and retains the advantages of length variable angle chain code; when occupying the same storage quantity, it can achieve better effect on retaining the corner of larger curvature. This method leaves out the small floatation of curve and it has a positive effect on angle feature and linear feature extraction. The authors used the method to extract the feature of image for dock detection, extracted the geometric feature based on the coastline, and marked out the dock areas combining the geometric feature with the existing knowledge. Experiments show this method can effectively extract right angle and parallel features.

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    Remote sensing bathymetric inversion for the Xisha Islands based on WorldView-2 data: A case study of Zhaoshu Island and South Island
    LI Li
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 170-175.   DOI: 10.6046/gtzyyg.2016.04.26
    Abstract   HTML   PDF (5367KB) ( 791 )

    Taking the WorldView-2 satellite data as sources, the author carried out depth study in the Xisha Islands, with the Zhaoshu Island and the South Island as test areas. The author first analyzed the correlation between the measured water depth and each band and then chose the most relevant band and band combination. It is shown that the coast band with green band ratio is the ideal combination for water depth extraction. Based on varying regression fitting analysis, the author determined the best fitting way that could achieve the best fitting precision in comparison with the real survey depth. At last, the model was used to conduct depth inversion of the South Island, and it is shown that water depth inversion root mean square error is less than 1.5 m, and the biggest relative error is within 0.26 m.

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    Research on lithological information enhancement method based on WorldView2 data: A case study of Zhagawusu district in Inner Mongolia
    WANG Pingping, TIAN Shufang
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 176-184.   DOI: 10.6046/gtzyyg.2016.04.27
    Abstract   HTML   PDF (11855KB) ( 339 )

    In order to further explore and discuss the application of lithologic information enhancement method in the lithologic remote sensing interpretation, the authors selected the Zhagawusu district of Sauron Mountain in Inner Mongolia as the research area for studying lithologic remote sensing information enhancement method. To tackle the problems such as complex rock image characteristics, weak color contrast and a few details caused by the factor of the same spectra with different objects, the same object with different spectra, and the coverage of the surface of the rock, the authors analyzed the rock spectral curve features, the WorldView2 spectral features and spatial features in the study area. On the basis of geometric correction and image fusion of WorldView2 data preprocessing, the authors used a series of effective methods for the remote sensing lithologic information enhancement based on spectral characteristics and spatial characteristics. Based on these methods, the authors made the lithologic interpretation of the study area. Comparing the results of interpretation with 1∶50 000 geological map in the study area shows that the results of interpretation have more lithologic types, improve the accuracy of the lithologic interpretation and thus provide the basis for a more accurate remote sensing lithologic identification.

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    Snow cover remote sensing monitoring in the west of Ngari area in northern Tibet from 2013 to 2014
    YAN Yunpeng, LIU Gang, LIU Jianyu, HAN Cong, ZHAO Zixian
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 185-190.   DOI: 10.6046/gtzyyg.2016.04.28
    Abstract   HTML   PDF (2515KB) ( 838 )

    Based on medium resolution satellite remote sensing(RS) data Landset ETM and OLI from 2013 to 2014, the authors conducted snow cover RS monitoring in the west of Ngari area in northern Tibet. Changing characteristics of snow-covered area over the two years were summed up by utilizing the statistical calculation method. Using the air temperature data, the authors studied in detail the corresponding rule between the snow-covered area changes and the air temperature value changes. Some conclusions have been reached: Every year the maximum period of the snow-covered area is from January to February, about 10 days before or after the beginning of spring. The maximum percentage of the snow-covered area reaches 80.82 percent. The minimum period of the snow-covered area is August, about 10 days before or after the beginning of autumn. The minimum percentage of the snow-covered area is only 0.77 percent. Annually, the decrease from the maximum percentage of the snow-covered area to the minimum percentagelasts for 6-7 months, which is a relatively gradual process. In the second stage, there is a fluctuation percentage of the snow-covered area for about 4-5 months. At last, the increase from the fluctuation percentage to the maximum percentage is a relatively drastic process lasting for 1 month or so.

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    Calculation of land consolidation potential of rural residential land on different models of land consolidation
    ZOU Yafeng, LYU Changhe, BAI Zhenhao, WANG Haiying
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 191-196.   DOI: 10.6046/gtzyyg.2016.04.29
    Abstract   HTML   PDF (2515KB) ( 808 )

    Calculation of land consolidation potential of rural residential land is an essential part of land consolidation planning. Based on the different potential calculation methods for different consolidation models, the authors designed the process and the model for calculating the rural residential land consolidation potential with Binyang county as a study case. According to the areas of different rural residential lands and the numbers of the household, classification is performed for different types of consolidations of rural residential land, which are named central village, maintaining village and minor residential area. The calculation model of consolidation potential of rural residential land is constructed, and the improvement measures are proposed. The method for determining the correction coefficient of potential calculation is put forward through the analysis of the social survey results, and the vacant construction land rate method is improved by GIS spatial analysis. The results show that the released potential of Binyang is 486.07 hm2 by 2020 through rural residential land consolidation. It is concluded that the process and the calculation model are reasonable and feasible.

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    GIS
    Description method for complex constraint of mine remote sensing monitoring attribute data
    DIAO Mingguang, XUE Tao, LIANG Jiandong, LI Jiancun, LIU Qiong
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 197-201.   DOI: 10.6046/gtzyyg.2016.04.30
    Abstract   HTML   PDF (2266KB) ( 575 )

    To tackle the description problems of XSD in the remote sensing attributes data of mine monitoring complex constraints, this paper proposes a method of "additional attributes". The XSD constraint description mechanism is extended, which includes element self-domain value description and the description between the elements. By using DOM to interpret and analyze the XSD file, the real-time verification of the attribute data is realized, which improves the user's working efficiency and the accuracy of attribute data assignment.

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    Exploring management and service mode for remote sensing data in big data era
    CHENG Tao
    REMOTE SENSING FOR LAND & RESOURCES. 2016, 28 (4): 202-206.   DOI: 10.6046/gtzyyg.2016.04.31
    Abstract   HTML   PDF (2526KB) ( 741 )

    A new service mode is explored and proposed oriented to big data era on the basis of analyzing the limitations of the existing massive remote sensing data's management and service mode. It takes national satellite remote sensing data acquired in the project of national basic aerial photography until the end of 2011 as the research example. Based on spatial overlap analyzing and statistical calculating, a new derivative product is made, which can reveal covering frequency and distribution of remote sensing data and provide a further service for users. The results show that the proposed service explores efficient mode and has the potential to help researchers to grasp comprehensive covering status of remote sensing data under the situation of big data era. Based on the spatial analyzing results, users' requirements and submitting orders could be confirmed rapidly, which improves the retrieval and access efficiency and raises the management and service level of massive remote sensing data.

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